AI ML Architect
Tasks
- Align machine learning strategy with business objectives
- Build vector database powered retrieval systems
- Define end-to-end AI ML architecture
- Design Gen AI model training and inference pipelines
- Design enterprise AI systems
- Drive cross functional collaboration for ML use cases
- Ensure ethical and responsible AI practices
- Evaluate build vs buy decisions for AI platforms
- Guide MLOps for model versioning monitoring and CI CD
- Implement retrieval augmented generation systems
- Integrate generative AI using LLM APIs
- Lead solution design discussions for AI ML architectures
- Mentor ML data and solution engineering teams
- Recommend AI technology adoption strategies
Perks/Benefits
- Flexible work schedule
- Generous time off
- Mental Health plans
- Remote-first work environment
- Wellbeing focused time
Skills/Tech-stack
AWS SageMaker | Azure Machine Learning | CI/CD | Deep learning | Docker | Embeddings | Faiss | Fine Tuning | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Kubeflow | Kubernetes | Language Models | Large Language Models | MLflow | Machine Learning | Model Monitoring | Model versioning | OpenAI API | Pinecone | Prompt engineering | PyTorch | Python | Retrieval-Augmented Generation | Scikit-learn | TensorFlow | Vector Databases | Vertex AI | Weaviate | XGBoost
Education
Roles
AI | AI/ML Architect | Architect | Learning Architect | ML Architect | Machine Learning Architect
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